Multi-scale Analysis of DSCOVR Data Using Wavelet Cross Correlation

Abstract:

The Deep Space Climate Observatory (DSCOVR), launched February 11^th 2015, makes the fastest combined measurements of solar wind magnetic field vectors and ion velocity distribution functions ever. These data allow us to search for correlation between ion and magnetic field fluctuations at kinetic ion scales for the first time. We present first results of a wavelet correlation analysis, which allows us to search for wave-particle interactions while accounting for different sampling cadences and data gaps. Using different wavelet algorithms we circumvent these issues and decompose the covariance and correlation between these two data streams on a scale by scale basis. We then generalize these quantities to wavelet cross-correlation and cross-covariance to identify interactions between charged particles and magnetic fields on kinetic scales. The techniques developed in this work will be directly applicable to plasma and magnetic field observations in the corona on the upcoming Solar Probe Plus mission.